MENLO PARK, Calif., Sept. 4, 2024 /PRNewswire/ -- Cyngn Inc. (the "Company" or "Cyngn") (Nasdaq: CYN) today announced the official granting of a new patent, U.S. Patent No. 12,032,099, which introduces a method to maintain the accuracy of data collected by an autonomous vehicle's sensors as the vehicle moves.
At its core, the patent optimizes sensor data processing by integrating advanced LiDAR and image technologies. By initially capturing comprehensive environmental data, the system then calculates and adjusts for any time delay between data acquisition and processing. Crucially, it dynamically generates a motion model based on real-time sensor movements across multiple axes, ensuring precise predictions of future positions.
The significance of this patent lies in its ability to significantly enhance the reliability and precision of sensor data in autonomous vehicles and robotics by effectively compensating for motion during data processing. This capability enables these systems to operate with utmost accuracy in dynamic environments, ultimately enhancing safety, efficiency, and empowering better-informed decisions based on precise environmental data.
"The granting of our 20th U.S. patent underscores Cyngn's ongoing commitment to advancing autonomous vehicle technologies," said Lior Tal, Chairman and Chief Executive Officer of Cyngn. "Following the 16 U.S. patents granted in 2023, this achievement reflects our team's commitment to building out a robust patent portfolio to protect our intellectual property."
The grant of this patent marks a significant milestone in Cyngn's intellectual property strategy, further bolstering its position in the AV industry. This success follows Cyngn's recent patent issuance announcement for Patent 19.
Cyngn provides its customers a seamless way to adopt self-driving technology into their operations without high upfront costs.
Previous patents include:
Patent Number | Title | Publication Date | |
20. | US-12,032,099-B2 | ADAPTIVE MOTION COMPENSATION OF PERCEPTION CHANNELS | 07/09/2024 |
19. | US-11,851,074-B2 | SYSTEM AND METHODS OF LARGE-SCALE AUTONOMOUS DRIVING VALIDATION | 12/26/2023 |
18. | US-11,837,090-B2 | SYSTEM AND METHODS OF ADAPTIVE TRAFFIC RULE-BASED DECISION MAKING FOR AUTONOMOUS DRIVING | 12/5/2023 |
17. | US-11,837,089-B2 | MODULAR EXTENSIBLE BEHAVIORAL DECISION SYSTEM FOR AUTONOMOUS DRIVING | 12/5/2023 |
16. | US-11,767,034-B2 | SYSTEM AND METHOD OF COMPUTATION ACCELERATION FOR AUTONOMOUS DRIVING SYSTEMS | 9/26/2023 |
15. | US-11,760,368-B2 | SYSTEM AND METHOD OF SAME-LOOP ADAPTIVE SIMULATION FOR AUTONOMOUS DRIVING | 9/19/2023 |
14. | US-11,747,454-B2 | GRANULARITY-FLEXIBLE EXISTENCE-BASED OBJECT DETECTION | 9/5/2023 |
13. | US-11,745,762-B2 | SYSTEM AND METHODS OF ADAPTIVE TRAJECTORY PREDICTION FOR AUTONOMOUS DRIVING | 9/5/2023 |
12. | US-11,745,747-B2 | SYSTEM AND METHOD OF ADAPTIVE DISTRIBUTION OF AUTONOMOUS DRIVING COMPUTATIONS | 9/5/2023 |
11. | US-11,745,750-B2 | SYSTEM AND METHOD OF LARGE-SCALE AUTOMATIC GRADING IN AUTONOMOUS DRIVING USING A DOMAIN-SPECIFIC LANGUAGE | 9/5/2023 |
10. | US-11,679,726-B2 | VEHICLE SENSOR SYSTEMS | 6/20/2023 |
9. | US-11,673,577-B2 | SYSTEM AND METHODS OF ADAPTIVE RELEVANCY PREDICTION FOR AUTONOMOUS DRIVING | 6/13/2023 |
8. | US-11,668,833-B2 | OBSTACLE DETECTION SYSTEMS | 6/6/2023 |
7. | US-11,651,583-B2 | MULTI-CHANNEL OBJECT MATCHING | 5/16/2023 |
6. | US-11,614,527-B2 | SELF-ADAPTIVE LIDAR-CAMERA SYNCHRONIZATION SYSTEM | 3/28/2023 |
5. | US-11,592,565-B2 | FLEXIBLE MULTI-CHANNEL FUSION PERCEPTION | 2/28/2023 |
4. | US-11,555,928-B2 | THREE-DIMENSIONAL OBJECT DETECTION WITH GROUND REMOVAL INTELLIGENCE | 1/17/2023 |
3. | US-11,372,115-B2 | VEHICLE LOCALIZATION | 6/28/2022 |
2. | US-11,186,234-B2 | VEHICLE SENSOR SYSTEMS | 11/30/2021 |
1. | US-11,169,271-B2 | OBSTACLE DETECTION SYSTEMS | 11/9/2021 |
For a comprehensive view of Cyngn's patents focused on modularity and flexibility of autonomous vehicle systems with multiple sensor modalities and configurations, please visit the USPTO.
About Cyngn
Cyngn develops and deploys scalable, differentiated autonomous vehicle technology for industrial organizations. Cyngn's self-driving solutions allow existing workforces to increase productivity and efficiency. The Company addresses significant challenges facing industrial organizations today, such as labor shortages, costly safety incidents, and increased consumer demand for eCommerce.
Cyngn's DriveMod Kit can be installed on new industrial vehicles at end of line or via retrofit, empowering customers to seamlessly adopt self-driving technology into their operations without high upfront costs or the need to completely replace existing vehicle investments.
Cyngn's flagship product, its Enterprise Autonomy Suite, includes DriveMod (autonomous vehicle system), Cyngn Insight (customer-facing suite of AV fleet management, teleoperation, and analytics tools), and Cyngn Evolve (internal toolkit that enables Cyngn to leverage data from the field for artificial intelligence, simulation, and modeling).
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Investor Contact:
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Forward-Looking Statements
This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. Any statement that is not historical in nature is a forward-looking statement and may be identified by the use of words and phrases such as "expects," "anticipates," "believes," "will," "will likely result," "will continue," "plans to," "potential," "promising," and similar expressions. These statements are based on management's current expectations and beliefs and are subject to a number of risks, uncertainties and assumptions that could cause actual results to differ materially from those described in the forward-looking statements, including the risk factors described from time to time in the Company's reports to the SEC, including, without limitation the risk factors discussed in the Company's annual report on Form 10-K filed with the SEC on March 7, 2024. Readers are cautioned that it is not possible to predict or identify all the risks, uncertainties and other factors that may affect future results No forward-looking statement can be guaranteed, and actual results may differ materially from those projected. Cyngn undertakes no obligation to publicly update any forward-looking statement, whether as a result of new information, future events, or otherwise.
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